NCT00001174 In order to better interpret the impact of genetic variation on the brain biology of bipolar disorder, we are pursuing a variety of functional genomics studies, including brain imaging, microarray gene expression and RNA-seq in post-mortem brain tissue, and cellular phenotyping of neurons derived from induced pluripotent stem cells. Current neuroimaging genetics work is focused on structural MRI. We contribute data to the ENIGMA brain imaging consortium, which is using genome-wide association methods in large samples to detect genetic markers associated with the volumes of various cortical and subcortical brain regions. These important endophenotypes may shed light on the mechanisms whereby common genetic variants influence risk for a variety of psychiatric disorders. Last year we carried out the first study to use the new technique of RNA-seq to characterize the transcribed portion of the genome (transcriptome) in post-mortem brain tissue. The resulting data were analyzed using several bioinformatics tools on high-performance computers at NIH. This study found that brain tissue from people with bipolar disorder showed dysregulated expression of several genes and transcripts that were involved in neuroplasticity, circadian rhythms, and cellular second-messenger systems. This year we extended the analysis to gene co-expression modules, which comprise large sets of genes whose expression is tightly correlated. This study supported the earlier work, but also identified additional genes that seem to play an important role in the pathogenesis of bipolar disorder. Genes involved in the postsynaptic density, a subcellular brain structure thought to be involved in neuronal signaling and synaptic plasticity, were especially enriched among those most strongly implicated in this study. In the coming year, we plan to carry out RNA-sequencing in an additional 200 postmortem brain samples obtained from people with mood disorders and matched comparison samples. This study will focus on the subgenual anterior cingulate cortex, which has been repeatedly implicated in people with mood disorders. We also seek to model the functional genomics of disease-related genes in cells derived from induced pluripotent stem cell (iPSC) lines. This project aims to explore the ways in which we can use iPSC technology to study the biological impact of genes and genetic mutations that we identify in our other ongoing studies. Working with the NIH Center for Regenerative Medicine and the National Institute of Neurological Disorders and Stroke (NINDS) stem cell core we have so far successfully reprogrammed fibroblasts from eight individuals ascertained in our ongoing family studies of bipolar disorder. We are also studying lines reprogrammed in collaborating labs. We are differentiating the cells into neurons and glia, and characterizing their morphology, action potentials, gene expression profiles, and response to medications and toxins. Careful analysis of these phenotypes could reveal differences between control and patient-derived cells, but we are also exploring ways to measure the functional impact of genetic mutations at the cellular level and to use genome editing tools such as CRISPR to rescue cellular phenotypes and establish a causal role for specific genetic mutations. This experimental system may also provide a way to characterize the biological impact of common risk alleles identified by genome-wide association studies. For example, we have recently shown that a common allele near the gene TRANK1 that has been repeatedly associated with bipolar disorder and schizophrenia leads to a significant reduction in TRANK1 gene expression in iPSC-derived neural progenitor cells that is largely reversed by chronic treatment with valproic acid at dosages that are therapeutic in people with bipolar disorder. We are currently investigating the mechanism of this phenomenon and ways in which we can use these findings to help identify novel treatments for bipolar disorder.